• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.22-28
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• 2008

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression. Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using existing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.1-13
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• 2016

The many researches on context-aware service based on the combination of semantic technology and IoT environment are being actively done. However, the previous study exploiting ontology has limitations not to accommodate the service requirement changes due to ontology prebuilt by specific service scenario. Although the concept of cross vertical ontology has emerged in order to overcome the limitation, it has other limitations that need additional components composing service environment for expressing context information and can't represent state information of environment elements. To cope with these limitations, we propose SISO (Semantic-based IoT Service Ontology) that can represent the states of environmental element without the need for additional context-information element. To verify SISO's characteristics, we select the service scenario and present applied results. The qualitative analysis comparing with the previous study is also presented by the applied results of service scenario.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.15-26
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• 2008

Recently, Internet Protocol TV technology has a latent power for searching information by using internet-connected interactive TV media. It is hard to browse and search web site conveniently since the visual and input devices are not sufficient for navigating through the websites. Zoomable user interface is a possible solution that may reduce users' task load and improve their performance. In this paper, we made three types of web browsers as scroll, physical zooming and semantic zooming type. Fifteen participants asked to do searching tasks and their task time, accuracy and subjective responses are recorded. In the result, though scroll type is evaluated more efficient than other types in task time and accuracy since participants are familiar with scroll type interface, semantic zooming type is highly rated in subjective responses such as perceived searching efficiency, satisfaction and joyfulness. This result implied semantic zooming is a possible solution which is improving user experience of searching websites using Internet Protocol TV.

• Journal of Information Management
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• v.40 no.1
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• pp.133-156
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• 2009

In this study, we link informal Web resources to KISTI NDSL's collections using automatic semantic indexing and tagging to examine the possibility of the service which recommends related documents using the similarity between KISTI's formal information resources and informal web resources. We collect and index Web resources and make automatic semantic linking through STEAK with KISTI's collections for NDSL retrieval. The macro precision which shows retrieval precision per a subject category is 62.6% and the micro precision which shows retrieval precision per a query is 66.9%. The experts' evaluation score is 76.7. This study shows the possibility of semantic linking NDSL retrieval results with Web information resources and expanding information services' coverage to informal information resources.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.1-12
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• 2019

Unlike existing Open APIs, Linked Data are made as a huge intelligent base to perform high-level SPARQL queries, and it is possible to create efficiently a new content by mashuping different information from various datasets. This paper implements a responsive web application for location-based semantic search. We mashup DBpedia, a kind of Linked Data, and GoogleMap API provided by Google, and provide a semantic browser function to confirm detail information regarding retrieved objects. Our system can be used in various access environments such as PC and mobile by applying responsive web design idea. The system implemented in this paper compares functional specifications with existing systems with similar functions. The comparison results show the superiority of our system in various aspects such as using semantic, linked-based browser, and mashup function.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.324-331
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• 1999

본 논문은 한국어의 특수조사, 특히 '도'의 의미, 문맥적 기능에 대하여 다루고 있다. '도'는 문맥의 자연스러운 연결에 있어서 중요한 역할을 수행한다. '도'가 쓰인 문장의 배경에는 반드시 일정한 전제가 존재한다. 전제는 그 문장의 의미 뿐만 아니라 기존 문맥과도 직접적으로 연관된다. 본 논문에서는 '같음', '유사함', '극한', '첨가' 및 병렬문에서 쓰이는 다섯 가지 '도'의 기능에 대하여 설명하고, alternatives semantics를 이용하여 이를 결합범주문법(CCG)에서 구현하는 방법을 제시한다.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.36-49
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• 2005

Recently, many researchers have given high attention to the semantic web services based on the semantic web technology While existing web services use the XML-based web service description language, WSDL, semantic web services are utilizing web service description languages such as DAML-S in ontology languages. The researchers of semantic web services are generally focused on web service discovery, web service invocation, web service selection and composition, and web service execution monitoring. Especially, the semantic web service discovery as the basis to accomplish the ultimate semantic web service environment has some different properties from previous information discovery areas. Hence, it is necessary to develop the storage system and discovery mechanism appropriate to the semantic well description languages. Even though some related systems have been developed, they are not appropriate for the embedded system environment, such as intelligent robotics, in which there are some limitations on memory disk space, and computing power In this regard, we in the embedded system environment have developed the document management system which efficiently manages the web service documents described by DAML-S for the purpose of the semantic web service discovery, In addition, we address the distinguishing characteristics of the system developed in this paper, compared with the related researches.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.1-25
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• 2008

Spoken dialog tasks incur many errors including speech recognition errors, understanding errors, and even dialog management errors. These errors create a big gap between the user's intention and the system's understanding, which eventually results in a misinterpretation. To fill in the gap, people in human-to-human dialogs try to clarify the major causes of the misunderstanding to selectively correct them. This paper presents a method of clarification techniques to human-to-machine spoken dialog systems. We viewed the clarification dialog as a two-step problem-Belief confirmation and Clarification strategy establishment. To confirm the belief, we organized the clarification process into three systematic phases. In the belief confirmation phase, we consider the overall dialog system's processes including speech recognition, language understanding and semantic slot and value pairs for clarification dialog management. A clarification expert is developed for establishing clarification dialog strategy. In addition, we proposed a new design of plugging clarification dialog module in a given expert based dialog system. The experiment results demonstrate that the error verifiers effectively catch the word and utterance-level semantic errors and the clarification experts actually increase the dialog success rate and the dialog efficiency.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.159-164
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• 1999

Homogeneous but distinct visual objects having low-contrast boundaries are usually merged in most of the segmentation algorithms. To alleviate this problem, an efficient image segmentation algorithm based on a bottom-up approach is proposed by using spatial domain information only. For initial image segmentation, we adopt an efficient marker extraction algorithm conforming to the human visual system. Then, two region-merging algorithms are successively applied so that homogeneous visual objects can be represented as simple as possible without destroying low-contrast real boundaries among them. The resultant segmentation describes homogeneous visual objects with few regions while preserving semantic object shapes well. Finally, a size-based region decision procedure may be applied to represent complex visual objects simpler, if their precise semantic contents are not necessary. Experimental results show that the proposed image segmentation algorithm represents homogeneous visual objects with a few regions and describes complex visual objects with a marginal number of regions with well-preserved semantic object shapes.

• Journal of Information Management
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• v.37 no.4
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• pp.93-104
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• 2006

With the advancement of internet and video compression technology, there has been an increasing demand for video, and producted a large quantity contents of UCC. Therefore, Semantic-sensitive retrieval and construction for digital video library is more in demand than ever. However, it is extremely difficult to categorize and label scenes in any video automatically for searching wanted scene. This study proposes a method to extract certain scenes and analyze the video content, and shows the experimental results after categorizing 5 sports news(soccer, baseball, golf, basketball, and volleyball).